Buddy tracking - efficient proximity detection among mobile friends
Pervasive and Mobile Computing
Preventing Location-Based Identity Inference in Anonymous Spatial Queries
IEEE Transactions on Knowledge and Data Engineering
Spatial generalisation algorithms for LBS privacy preservation
Journal of Location Based Services - Privacy Aware and Location-Based Mobile Services
Privacy-Aware Proximity Based Services
MDM '09 Proceedings of the 2009 Tenth International Conference on Mobile Data Management: Systems, Services and Middleware
Louis, Lester and Pierre: three protocols for location privacy
PET'07 Proceedings of the 7th international conference on Privacy enhancing technologies
An attacker's view of distance preserving maps for privacy preserving data mining
PKDD'06 Proceedings of the 10th European conference on Principle and Practice of Knowledge Discovery in Databases
Anonymous user tracking for location-based community services
LoCA'06 Proceedings of the Second international conference on Location- and Context-Awareness
The VLDB Journal — The International Journal on Very Large Data Bases
A privacy preserving system for friend locator applications
Proceedings of the 9th ACM international symposium on Mobility management and wireless access
Location privacy attacks based on distance and density information
Proceedings of the 20th International Conference on Advances in Geographic Information Systems
Private proximity testing with an untrusted server
Proceedings of the sixth ACM conference on Security and privacy in wireless and mobile networks
Private proximity detection for convex polygons
Proceedings of the 12th International ACM Workshop on Data Engineering for Wireless and Mobile Acess
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A "friend finder" is a Location Based Service (LBS) that informs users about the presence of participants in a geographical area. In particular, one of the functionalities of this kind of application, reveals the users that are in proximity. Several implementations of the friend finder service already exist but, to the best of our knowledge, none of them provides a satisfactory technique to protect users' privacy. While several techniques have been proposed to protect users' privacy for other types of spatial queries, these techniques are not appropriate for range queries over moving objects, like those used in friend finders. Solutions based on cryptography in decentralized architectures have been proposed, but we show that a centralized service has several advantages in terms of communication costs, in addition to support current business models. In this paper, we propose a privacy-aware centralized solution based on an efficient three-party secure computation protocol, named Longitude . The protocol allows a user to know if any of her contacts is close-by without revealing any location information to the service provider. The protocol also ensures that user-defined minimum privacy requirements with respect to the location information revealed to other buddies are satisfied. Finally, we present an extensive experimental work that shows the applicability of the proposed technique and the advantages over alternative proposals.